Run-Time Speculative Parallelization --
We have developed efficient run-time and static analysis techniques
to enable efficient run-time parallelization on loops with irregular
and sparse memory access patterns
[CC'00,
LCPC'99].
Now, a small team in our research group
are at the late stage of
integrating various run-time speculative parallelization techniques
- LRPD test,
Sparse LRPD test,
Recursive LRPD test and
static analysis techniques - into a Hybrid Analysis
framework through exploring most
available partial static information at compile-time and therefore
to reduce run-tiem work.

Adaptive Algorithm Selection and Its Application on Parallelizing Irregular Reductions --
We have developed a systematic technology which allows dynamic program
to pick the most appropriate algorithm at run-time. The model is
derived from synthetic experiments running on seperated synthetic loops. We have
applied this technology on adaptive reduction parallelization and
extensive experiments have been carried out on both static irregular programiand
dynamic irregular programs (patterns change on-the-fly).
[ICS'00,
LCPC'02].